THE HIDDEN UNCERTAINTY

Mapping measurement challenges in Alaska’s vanishing glaciers

30DayChartChallenge
Data Visualization
R Programming
2025
An exploration of measurement uncertainty in Alaska’s glaciers from 1946-2023, visualized in National Geographic style. This visualization reveals how distance from observation points, glacier size, and remote locations contribute to measurement challenges in tracking glacier changes across different Alaskan regions.
Published

April 30, 2025

Figure 1: A map showing uncertainty in Alaska glacier measurements. Three distinct regions of glaciers are labeled, with colors ranging from yellow (low uncertainty) to purple (high uncertainty). An information box explains that uncertainty is affected by distance from observation points, glacier size, and remote locations. The visualization has the distinctive yellow border of National Geographic style.

Steps to Create this Graphic

1. Load Packages & Setup

Show code
## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
pacman::p_load(
  tidyverse,          # Easily Install and Load the 'Tidyverse'
  ggtext,             # Improved Text Rendering Support for 'ggplot2'
  showtext,           # Using Fonts More Easily in R Graphs
  janitor,            # Simple Tools for Examining and Cleaning Dirty Data
  skimr,              # Compact and Flexible Summaries of Data
  scales,             # Scale Functions for Visualization
  lubridate,          # Make Dealing with Dates a Little Easier
  ggdist,             # Visualizations of Distributions and Uncertainty 
  sf,                 # Simple Features for R
  rnaturalearth,      # World Map Data from Natural Earth
  rnaturalearthdata,  # World Vector Map Data from Natural Earth Used in 'rnaturalearth'
  viridis,            # Colorblind-Friendly Color Maps for R
  ggnewscale,         # Multiple Fill and Colour Scales in 'ggplot2'
  ggrepel,            # Automatically Position Non-Overlapping Text Labels with 'ggplot2'
  camcorder       # Record Your Plot History
  )
})

### |- figure size ----
gg_record(
    dir    = here::here("temp_plots"),
    device = "png",
    width  = 10,
    height = 10,
    units  = "in",
    dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))

2. Read in the Data

Show code
alaska_combined <- readRDS(
  here::here(
    "data/30DayChartChallenge/2025/alaska_combined_data.rds")) |> 
  clean_names()

3. Examine the Data

Show code
glimpse(alaska_combined)
skim(alaska_combined)

4. Prep Data

For the data preparation step, refer to the data_preparation.R file in my GitHub repository.

4.1 Tidy Data

Show code
### |- Tidy ----
# Base map data
world <- ne_countries(scale = "medium", returnclass = "sf")
alaska_bounds <- st_bbox(c(
  xmin = -170, ymin = 55, xmax = -130, ymax = 70), crs = st_crs(4326)
  )

# Calculate average error per glacier over all years 
glacier_avg_error <- alaska_combined |>
  group_by(rgi_id, region, cen_lon, cen_lat, area) |>
  summarize(
    mean_error = mean(error_estimate, na.rm = TRUE),
    mean_dist = mean(mean_dist_gla_anom, na.rm = TRUE),
    .groups = "drop"
  )

# Convert to SF for mapping
glacier_error_sf <- glacier_avg_error |>
  st_as_sf(coords = c("cen_lon", "cen_lat"), crs = 4326)

# Define regions 
region_points <- tibble(
  region_id = c("Region 1", "Region 2", "Region 3"),          
  lon = c(-166, -142, -158),
  lat = c(56.5, 62, 69),
  color = c("gray20", "gray20", "gray20")  
)

# Convert to SF for plotting
region_points_sf <- st_as_sf(
  region_points, coords = c("lon", "lat"), crs = 4326
  )

# Create informational box 
# Extract uncertainty statistics
uncertainty_stats <- glacier_avg_error |>
  summarize(
    mean_error = mean(mean_error, na.rm = TRUE),
    max_error = max(mean_error, na.rm = TRUE),
    min_error = min(mean_error, na.rm = TRUE),
    glacier_count = n()
  )

# Textbox
info_box_text <- paste0(
  "UNCERTAINTY FACTORS\n\n",
  "• Distance from observation points\n",
  "• Small glaciers (<1 km²)\n",
  "• Remote mountain locations\n",
  "• Avg. measurement error: ", round(uncertainty_stats$mean_error, 2), " m w.e.\n",
  "• Total glaciers: ", uncertainty_stats$glacier_count
)

5. Visualization Parameters

Show code
### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = c(
    "water" = "#71ABD8",       
    "land" = "#E8E6D9",       
    "glacier" = "#D1E6EC",     
    "highlight" = "#FFCD00",   
    "text" = "#000000",        
    "uncertainty" = "#8BB9DD", 
    "dark_blue" = "#1A5088",   
    "text_gray" = "#555555"    
    )
  )          
 
### |-  titles and caption ----
# text
title_text    <- str_glue("THE HIDDEN UNCERTAINTY")

subtitle_text <- str_glue("Mapping measurement challenges in Alaska's vanishing glaciers\n
                          Color indicates average error estimate magnitude (1946-2023)")

caption_text <- create_dcc_caption(
  dcc_year = 2025,
  dcc_day = 30,
  source_text =  "World Glacier Monitoring Service" 
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----

# National Geographic theme (at least my interpretation)
theme_natgeo <- function() {
  theme_minimal(base_size = 14) +
    theme(
      # Text elements
      plot.title = element_text(face = "bold", size = 20, family = "sans"),
      plot.subtitle = element_text(size = 14, family = "sans", margin = margin(b = 20)),
      axis.title = element_text(face = "bold", size = 10),
      legend.title = element_text(face = "bold", size = 10),
      
      # Grid elements
      panel.grid.major = element_line(color = "gray90", size = 0.2),
      panel.grid.minor = element_blank(),
      
      # Background elements
      plot.background = element_rect(fill = "white", color = NA),
      panel.background = element_rect(fill = "white", color = NA),
      
      # Margins and spacing
      plot.margin = margin(20, 20, 20, 20),
      legend.margin = margin(10, 10, 10, 10),
      
      # Caption styling
      plot.caption = element_text(size = 9, hjust = 0, color = colors$palette["text_gray"], 
                                  margin = margin(t = 15))
    )
}

6. Plot

Show code
### |-  Plot ----
# Main map -----
main_map <- ggplot() +
  # Base map
  geom_sf(data = world, fill = colors$palette['land'], color = "gray70") +
  
  # Geoms
  geom_sf(
    data = glacier_error_sf, 
    aes(size = area, color = mean_error),
    alpha = 0.8
    ) +
  geom_label(
    data = region_points_sf,
    aes(geometry = geometry, label = region_id),
    stat = "sf_coordinates",
    fill = "white",
    color = region_points$color, 
    fontface = "bold",
    size = 4,
    label.padding = unit(0.4, "lines"),
    label.r = unit(0.15, "lines"),
    alpha = 0.9,
    label.size = 0.8  
  ) +
  # Scales
  scale_color_viridis_c(
    name = "Mean Error\nEstimate (m w.e.)",
    option = "plasma",
    direction = -1,
    guide = guide_colorbar(
      title.position = "top",
      barwidth = 12,
      barheight = 1
    )
  ) +
  scale_size_continuous(
    name = "Glacier Area (km²)",
    range = c(0.1, 3.5),
    breaks = c(1, 10, 100, 1000),
    trans = "log10",
    labels = label_comma(),
    guide = guide_legend(
      title.position = "top",
      override.aes = list(color = colors$palette["dark_blue"])
    )
  ) +
  coord_sf(  # Alaska region
    xlim = c(alaska_bounds$xmin, alaska_bounds$xmax), 
    ylim = c(alaska_bounds$ymin, alaska_bounds$ymax)
  ) +
  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    x = NULL,
    y = NULL
  ) +
  # Theme
  theme_natgeo() +
  theme(

    legend.position = "bottom",
    legend.box = "horizontal",
    legend.direction = "horizontal",
    legend.spacing.x = unit(1, "cm"),
    legend.box.spacing = unit(0.5, "cm"),
    legend.key.size = unit(0.8, "cm"),

    plot.title = element_text(
      size = rel(2.6),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.90),
      family = fonts$subtitle,
      color = colors$subtitle,
      lineheight = 0.8,
      margin = margin(t = 5, b = 20)
    ),
    plot.caption = element_markdown(
      size = rel(0.65),
      family = fonts$caption,
      color = colors$caption,
      lineheight = 0.65,
      hjust = 0.5,
      halign = 0.5,
      margin = margin(t = 10, b = 5)
    ),
  )

# Info textbox -----
info_box <- ggplot() +
  annotate(
    "rect",
    xmin = 0, xmax = 1, ymin = 0, ymax = 1,
    fill = alpha(colors$palette["highlight"], 0.08)
  ) +
  annotate(
    "text",
    x = 0.05, y = 0.5,
    label = info_box_text,
    hjust = 0, vjust = 0.5,
    size = 3.2,  
    fontface = "plain",
    color = colors$palette["text"]
  ) +
  annotate(
    "rect",
    xmin = 0, xmax = 1, ymin = 0, ymax = 1,
    fill = NA, color = alpha(colors$palette["highlight"], 0.5),
    linewidth = 1
  ) +
  theme_void() +
  xlim(0, 1) + ylim(0, 1)

# Combine main map and info box -----
combined_map <- main_map +
  annotation_custom(
    grob = ggplotGrob(info_box),
    xmin = -143, xmax = -128,  
    ymin = 62.5, ymax = 68.5     
  )

# Final map -----
final_map <- combined_map +
  theme(
    plot.background = element_rect(
      fill = "white", 
      color = colors$palette["highlight"], 
      linewidth = 5
    )
  )

7. Save

Show code
### |-  plot image ----  
save_plot(
  final_map, 
  type = "30daychartchallenge", 
  year = 2025, 
  day = 30, 
  width = 10, 
  height = 10
  )

8. Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1              camcorder_0.1.0         ggrepel_0.9.6          
 [4] ggnewscale_0.5.1        viridis_0.6.5           viridisLite_0.4.2      
 [7] rnaturalearthdata_1.0.0 rnaturalearth_1.0.1     sf_1.0-19              
[10] ggdist_3.3.2            scales_1.3.0            skimr_2.1.5            
[13] janitor_2.2.0           showtext_0.9-7          showtextdb_3.0         
[16] sysfonts_0.8.9          ggtext_0.1.2            lubridate_1.9.3        
[19] forcats_1.0.0           stringr_1.5.1           dplyr_1.1.4            
[22] purrr_1.0.2             readr_2.1.5             tidyr_1.3.1            
[25] tibble_3.2.1            ggplot2_3.5.1           tidyverse_2.0.0        

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1     farver_2.1.2         fastmap_1.2.0       
 [4] pacman_0.5.1         digest_0.6.37        timechange_0.3.0    
 [7] lifecycle_1.0.4      rsvg_2.6.1           terra_1.7-83        
[10] magrittr_2.0.3       compiler_4.4.0       rlang_1.1.6         
[13] tools_4.4.0          utf8_1.2.4           yaml_2.3.10         
[16] knitr_1.49           labeling_0.4.3       htmlwidgets_1.6.4   
[19] curl_6.0.0           classInt_0.4-10      xml2_1.3.6          
[22] repr_1.1.7           KernSmooth_2.23-22   withr_3.0.2         
[25] grid_4.4.0           fansi_1.0.6          e1071_1.7-16        
[28] colorspace_2.1-1     cli_3.6.4            rmarkdown_2.29      
[31] ragg_1.3.3           generics_0.1.3       rstudioapi_0.17.1   
[34] httr_1.4.7           tzdb_0.5.0           commonmark_1.9.2    
[37] DBI_1.2.3            proxy_0.4-27         base64enc_0.1-3     
[40] vctrs_0.6.5          jsonlite_1.8.9       hms_1.1.3           
[43] systemfonts_1.1.0    magick_2.8.5         units_0.8-5         
[46] glue_1.8.0           gifski_1.32.0-1      codetools_0.2-20    
[49] distributional_0.5.0 stringi_1.8.4        gtable_0.3.6        
[52] munsell_0.5.1        pillar_1.9.0         htmltools_0.5.8.1   
[55] R6_2.5.1             textshaping_0.4.0    rprojroot_2.0.4     
[58] evaluate_1.0.1       markdown_1.13        gridtext_0.1.5      
[61] snakecase_0.11.1     renv_1.0.3           class_7.3-22        
[64] Rcpp_1.0.13-1        svglite_2.1.3        gridExtra_2.3       
[67] xfun_0.49            pkgconfig_2.0.3

9. GitHub Repository

The complete code for this analysis is available in 30dcc_2025_30.qmd.

For the full repository, click here.

10. References

  1. Data Sources:
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